Researches On Supply Chain Inventory Control And Distribution Under Stochastic Demands

Supply chain management works for material optimization as a method for enterprise strategies through correlative information system technology from raw material purchase to customer receiving goods. The aim is higher profit and higher customer satisfaction. Supply chain management is composed by scheme, purchase, manufacturing, transportation and return of goods, including product chain and information chain, not only marketing, but also customer prediction. Inventory control keeps the balance between supply and demands and reduces supply circle to avoid shortage. Meanwhile, inventory control regulates seasonal disturbances in the manufacturing and averages ordering costs. Work-in-process maintains the manufacturing continuity to avoid manufacturing interregnum. Due to the uncertainty of customer demands, this paper takes attentions on two aspects, inventory control and inventory distribution routing problem, to discuss supply chain inventory optimal problems under stochastic demands.The retails are in four parts:â‘ In the application of model predictive control for inventory control, inventories communication isn't taken into account, inventory strategies of each echelon haven't any contact with each others. Cooperative model predictive control for inventory control is presented to solve the communication among supply chain inventory nodes through structuring objective function. While building the inventory strategy, the other storage information should be utilized to raise total profit.â‘¡For the uncertain order lead time and product lead time in the supply chain inventory control, time-stamping predictive control for inventory control is proposed to control inventory disturbance and fit customer satisfaction. At each sample time, updating the modified matrix is for supply chain inventory updating. The modified matrix consists of uncertain ordering lead time and constant manufacturing lead time. The simulated results show the well performances on inventory control under stochastic demands. Meanwhile, while order lead time and product lead time follows normal distributions, the robustness is still well.â‘¢For supply chain inventory control model with stochastic lead time, improved time-stamped predictive control algorithm for inventory control under stochastic demands is proposed. The restraint conditions in the model are enhanced and random lead times are seen as system random delays. Updating matrix is restructured to constrain inventory disturbances and input fluctuations by random demands and lead time efficiently. Moreover, bullwhip effect leaded by random demands is reduced.â‘£For the distributions in the inventory control, the distribution routing optimal problem among one manufacturer and multiple retailers is discussed. A distributed multi-ant cooperation algorithm for routing problems is proposed for large scale capacitated vehicle routing problem. Tree-cut algorithm is utilized for decomposition and dimensionality reduction in the centralized problems. Distributed multi-ant cooperation searches the optimal solution and costs less time for large scale problems by considering objectives coupling and constraints coupling among sub-systems.Finally, conclusion is gained. Moreover, the disadvantages of the paper and the further researches in the future are pointed out.